Securing Your Internal Knowledge Amidst Shadow AI – KMWorld

Franz’s CEO, Dr. Jans Aasman was interviewed for this article on KMWorld.

Dr. Aasman was quoted:

The graph provides the same advantages for specific regulatory frameworks, security policies, and business rules. These boons can help compliance and governance personnel implement access controls, as well as dynamic agents tasked with the same thing. According to Franz CEO Jans Aasman, “The rise of Policy-as-Knowledge—encoding HIPAA, SOX, CMS, and AML rules as machine-checkable logic—will transform how AI agents act within regulated workflows. Instead of relying on human reviews or ad hoc filters, autonomous systems will reason over encoded policies before executing an action, much like compilers enforcing syntax before code runs.”

“Neuro-symbolic AI links language models to ontologies, rules, and provenance graphs, enabling real-time validation of whether a decision complies with institutional or legal frameworks,” Aasman observed. These capabilities can ensure that AI agents adhere to established data governance stipulations. They’re also useful for humans accessing or sharing information within and between different departments.

Incorporating knowledge graphs to manage the metadata obtained during the data discovery process has the added benefit of helping organizations overcome shadow AI, in which individuals use AI systems that haven’t been approved by their organizations. With the neuro-symbolic AI approach Aasman referenced, “LLMs will be the language layer, and neuro-symbolic is the cognitive operating system, governance reasoning layer. Symbolic structures will govern what agents know, can do, and must not do.” LLMs are the interface for users interacting with the knowledge graph. However, the symbolic structures (rules, ontologies, etc.) are primed for constraining the answers of retrieval-augmented generation (RAG) systems and language model interactions for question-answering, summarization, synthesis, and more.

Read the full article at KMWorld  – Securing Your Internal Knowledge Amidst Shadow AI